DocumentCode :
2871422
Title :
EOG guidance of a wheelchair using neural networks
Author :
Barea, Rafael ; Boquete, Luciano ; Mazo, Manuel ; López, Elena ; Bergasa, L.M.
Author_Institution :
Electron. Dept., Univ. of Alcala, Madrid, Spain
Volume :
4
fYear :
2000
fDate :
2000
Firstpage :
668
Abstract :
Presents a method to control and guide mobile robots. In this case, to send different commands we have used electrooculography (EOG) techniques, so that, control is made by means of the ocular position (eye displacement into its orbit). A neural network is used to identify the inverse eye model, therefore the saccadic eye movements can be detected and where the user is looking can be determined. This control technique can be useful in multiple applications, but in this work it is used to guide an autonomous robot (wheelchair) as a system to help to people with severe disabilities. The system consists of a standard electric wheelchair with an on-board computer, sensors and graphical user interface running on a computer
Keywords :
bioelectric potentials; eye; graphical user interfaces; handicapped aids; mobile robots; radial basis function networks; EOG guidance; autonomous robot; electric wheelchair; electrooculography techniques; eye displacement; inverse eye model; ocular position; severe disabilities; Application software; Computer interfaces; Control systems; Displacement control; Electrooculography; Inverse problems; Mobile robots; Neural networks; Robot sensing systems; Wheelchairs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
ISSN :
1051-4651
Print_ISBN :
0-7695-0750-6
Type :
conf
DOI :
10.1109/ICPR.2000.903006
Filename :
903006
Link To Document :
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